Validating hits from the epigenetic screening
Max Trauernicht
2020-05-01
knitr document van Steensel lab
Epigenetic Screening
Introduction
This script tries to find out which drugs are able to significantly alter indel pattern formation in RSTP2#5 cells in different chromatin contexts. In the end, the aim is to couple biological relevance to these changes.
Description of Data
How to make a good rendering table:
| column1 | column2 | column3 |
|---|---|---|
| 1 | 2 | 3 |
| a | b | c |
Data processing
Path, Libraries, Parameters and Useful Functions
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## ComplexHeatmap version 2.0.0
## Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
## Github page: https://github.com/jokergoo/ComplexHeatmap
## Documentation: http://jokergoo.github.io/ComplexHeatmap-reference
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## If you use it in published research, please cite:
## Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional
## genomic data. Bioinformatics 2016.
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## circlize version 0.4.8
## CRAN page: https://cran.r-project.org/package=circlize
## Github page: https://github.com/jokergoo/circlize
## Documentation: http://jokergoo.github.io/circlize_book/book/
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## If you use it in published research, please cite:
## Gu, Z. circlize implements and enhances circular visualization
## in R. Bioinformatics 2014.
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Functions used thoughout this script.
Data import
Compute relevant logratios and divide per concentration
Bring dataframe to heatmap plotting format
Annotate heatmap columns and rows
# Row annotation: annotate drugs with the target group
target <- indel.data[indel.data$Target != c("Negative Control", "MRN", "DNA-PK"),] %>%
select(Drug, Target) %>% unique() %>% remove_rownames %>%
column_to_rownames(var="Drug")## Warning in `!=.default`(indel.data$Target, c("Negative Control", "MRN", : longer
## object length is not a multiple of shorter object length## Warning in is.na(e1) | is.na(e2): longer object length is not a multiple of
## shorter object length# Add type of chr. mark (repressive or active)
type <- mapping_mean_long %>% select(variable, type) %>% unique() %>%
remove_rownames %>% column_to_rownames(var="variable")
# Add annotation of barcodes (based on clustering in 0_Clone5_Annotation.Rmd)
barcode.annotation <- unique(as.data.frame(indel.data.high$barcode))
## Manually added these tags: check/rewrite this
barcode.annotation$cluster[c(18,2)] <- "Active Promoter/Enhancer"
barcode.annotation$cluster[c(12,8)] <- "H3K9me2/3 Domain"
barcode.annotation$cluster[c(3,14,4,17)] <- "Active Gene Body"
barcode.annotation$cluster[c(5,13,6,15)] <- "LAD"
barcode.annotation$cluster[c(7,16)] <- "No Marks Present"
barcode.annotation$cluster[c(1,10,9,11)] <- "H3K27me3 Domain"
barcode.annotation <- barcode.annotation %>% remove_rownames() %>%
column_to_rownames("indel.data.high$barcode")
# Change colors of annotations
colors <- brewer.pal(length(unique(barcode.annotation$cluster)), "Pastel2")
names(colors) <- unique(barcode.annotation$cluster)
annotation_colors_scr = list(
cluster = colors,
type = c(Active="#669966", Repressive="grey90"),
target = c(HDAC="#60988D", HAT="#C6D0A8", Sirtuin="#8FCAAC",
HMT="#FDCDAC", DNMT="#D69C81", `Histone Demethylase`="#FFF2AE",
HIF="#E3DCD5", JAK="#C8D7E2", PIM="#9AB8C4", `Aurora Kinase`="#F4CAE4",
PARP="#CB546F", `Epigenetic Reader Domain`= "#476D61", `DNA-PK`="#E07A43"
))
# Order the annotation legend
ordered_marks <- c("Active Promoter/Enhancer", "Active Gene Body", "No Marks Present", "H3K27me3 Domain", "H3K9me2/3 Domain", "LAD")
annotation_colors_scr$cluster <- annotation_colors_scr$cluster[ordered_marks]
ordered_marks2 <- c("DNA-PK","Epigenetic Reader Domain", "HDAC", "Sirtuin", "HAT",
"Histone Demethylase", "HMT", "DNMT",
"HIF", "JAK", "PIM",
"Aurora Kinase", "PARP")
annotation_colors_scr$target <- annotation_colors_scr$target[ordered_marks2]Next, I want to create heatmaps to visualize the effect of each individual drug on each of the 18 barcodes.
Results
logratio heatmap of each individual drug vs. barcode
## This heatmap contains too much information -> We need to decrease the number of drugs ## Only drugs that change the logratio 
Now plot the same for the efficiency
Heatmap for one certain target group
# Annotate heatmaps with drug targets to display only certain drug target groups
## target.logratio.high
indel.data.high.drug2 <- rownames_to_column(indel.data.high.drug, "barcode") %>%
melt() %>% dcast(variable ~ barcode, value.var = "value")## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
## continue using melt methods from reshape2 while both libraries are attached,
## e.g. melt.list, you can prepend the namespace like reshape2::melt(.). In the
## next version, this warning will become an error.## Using barcode as id variables## Warning in dcast(., variable ~ barcode, value.var = "value"): The dcast
## generic in data.table has been passed a data.frame and will attempt to redirect
## to the reshape2::dcast; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. Please do this redirection yourself like
## reshape2::dcast(.). In the next version, this warning will become an error.targets <- unique(data.frame(indel.data %>% select(Target, Drug))) %>%
setnames(old = "Drug", new = "variable")
indel.data.high.drug2 <- merge(indel.data.high.drug2, targets) %>%
remove_rownames %>% column_to_rownames(var="variable")
target.logratio.high <- indel.data.high.drug2[-grep("Negative control|MRN|DNA-PK",indel.data.high.drug2$Target),]
## target.logratio.med
indel.data.med.drug2 <- rownames_to_column(indel.data.med.drug, "barcode") %>%
melt() %>% dcast(variable ~ barcode, value.var = "value")## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
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## next version, this warning will become an error.## Using barcode as id variables## Warning in dcast(., variable ~ barcode, value.var = "value"): The dcast
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## to the reshape2::dcast; please note that reshape2 is deprecated, and this
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## reshape2::dcast(.). In the next version, this warning will become an error.indel.data.med.drug2 <- merge(indel.data.med.drug2, targets) %>%
remove_rownames %>% column_to_rownames(var="variable")
target.logratio.med <- indel.data.med.drug2[-grep("Negative control|MRN|DNA-PK",indel.data.med.drug2$Target),]
## target.logratio.low
indel.data.low.drug2 <- rownames_to_column(indel.data.low.drug, "barcode") %>%
melt() %>% dcast(variable ~ barcode, value.var = "value")## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
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## e.g. melt.list, you can prepend the namespace like reshape2::melt(.). In the
## next version, this warning will become an error.## Using barcode as id variables## Warning in dcast(., variable ~ barcode, value.var = "value"): The dcast
## generic in data.table has been passed a data.frame and will attempt to redirect
## to the reshape2::dcast; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. Please do this redirection yourself like
## reshape2::dcast(.). In the next version, this warning will become an error.indel.data.low.drug2 <- merge(indel.data.low.drug2, targets) %>%
remove_rownames %>% column_to_rownames(var="variable")
target.logratio.low <- indel.data.low.drug2[-grep("Negative control|MRN|DNA-PK",indel.data.low.drug2$Target),]
## target.efficiency.high
indel.data.high.eff2 <- rownames_to_column(indel.data.high.eff, "barcode") %>%
melt() %>% dcast(variable ~ barcode, value.var = "value")## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
## continue using melt methods from reshape2 while both libraries are attached,
## e.g. melt.list, you can prepend the namespace like reshape2::melt(.). In the
## next version, this warning will become an error.## Using barcode as id variables## Warning in dcast(., variable ~ barcode, value.var = "value"): The dcast
## generic in data.table has been passed a data.frame and will attempt to redirect
## to the reshape2::dcast; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. Please do this redirection yourself like
## reshape2::dcast(.). In the next version, this warning will become an error.indel.data.high.eff2 <- merge(indel.data.high.eff2, targets) %>%
remove_rownames %>% column_to_rownames(var="variable")
target.eff.high <- indel.data.high.eff2[-grep("Negative control|MRN|DNA-PK",indel.data.high.eff2$Target),]
## target.efficiency.med
indel.data.med.eff2 <- rownames_to_column(indel.data.med.eff, "barcode") %>%
melt() %>% dcast(variable ~ barcode, value.var = "value")## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
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## e.g. melt.list, you can prepend the namespace like reshape2::melt(.). In the
## next version, this warning will become an error.## Using barcode as id variables## Warning in dcast(., variable ~ barcode, value.var = "value"): The dcast
## generic in data.table has been passed a data.frame and will attempt to redirect
## to the reshape2::dcast; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. Please do this redirection yourself like
## reshape2::dcast(.). In the next version, this warning will become an error.indel.data.med.eff2 <- merge(indel.data.med.eff2, targets) %>%
remove_rownames %>% column_to_rownames(var="variable")
target.eff.med <- indel.data.med.eff2[-grep("Negative control|MRN|DNA-PK",indel.data.med.eff2$Target),]
## target.efficiency.low
indel.data.low.eff2 <- rownames_to_column(indel.data.low.eff, "barcode") %>%
melt() %>% dcast(variable ~ barcode, value.var = "value")## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
## continue using melt methods from reshape2 while both libraries are attached,
## e.g. melt.list, you can prepend the namespace like reshape2::melt(.). In the
## next version, this warning will become an error.## Using barcode as id variables## Warning in dcast(., variable ~ barcode, value.var = "value"): The dcast
## generic in data.table has been passed a data.frame and will attempt to redirect
## to the reshape2::dcast; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. Please do this redirection yourself like
## reshape2::dcast(.). In the next version, this warning will become an error.indel.data.low.eff2 <- merge(indel.data.low.eff2, targets) %>%
remove_rownames %>% column_to_rownames(var="variable")
target.eff.low <- indel.data.low.eff2[-grep("Negative control|MRN|DNA-PK",indel.data.low.eff2$Target),]
# Choose from the above dfs what you want to display
## Only select HDACs
hdac.logratio <- target.eff.high[target.eff.high$Target=="HDAC",] %>%
select(-Target) %>% t()
# Generate pheatmap
# Use myBreaks5 for efficiency heatmap, myBreaks1 for logratio heatmap
pheatmap(as.matrix(hdac.logratio),
annotation_col = target,
annotation_row = barcode.annotation,annotation_legend = F,
color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdBu")))(100),
breaks = myBreaks5, cluster_rows = chip_dendogram$tree_col,
annotation_colors = annotation_colors_scr,
cellwidth = 14, cellheight = 14,
labels_row = c("Integration 15","Integration 1","Integration 5","Integration 6",
"Integration 10","Integration 9","Integration 13","Integration 3",
"Integration 17","Integration 16","Integration 18", "Integration 4",
"Integration 11","Integration 7","Integration 12", "Integration 14",
"Integration 8","Integration 2"),
main = "logratio change - 1uM of drugs added - HDACs only")
Efficiency/logratio overlay
## (polygon[GRID.polygon.194], polygon[GRID.polygon.195], polygon[GRID.polygon.196], polygon[GRID.polygon.197], text[GRID.text.198], text[GRID.text.199], text[GRID.text.200], text[GRID.text.201], text[GRID.text.202])Next step is to import the chromatin data to generate a correlation matrix between the logratio change of each drug and the chromatin data. A correlation is calculated by comparing logratio changes of drug A for each barcode with ChIP data of ChIP dataset A for each barcode etc.
Correlation between ChIP data and logratio changes
## Warning in melt(mapping_mean_chip, variable.name = "barcode", value.name =
## "mean"): The melt generic in data.table has been passed a data.frame and will
## attempt to redirect to the relevant reshape2 method; please note that reshape2
## is deprecated, and this redirection is now deprecated as well. To continue using
## melt methods from reshape2 while both libraries are attached, e.g. melt.list,
## you can prepend the namespace like reshape2::melt(mapping_mean_chip). In the
## next version, this warning will become an error.## Using ChIP as id variables## Warning in dcast(., barcode ~ ChIP, value.var = "mean"): The dcast generic
## in data.table has been passed a data.frame and will attempt to redirect
## to the reshape2::dcast; please note that reshape2 is deprecated, and this
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## reshape2::dcast(.). In the next version, this warning will become an error.
# There are some interesting drug-induced changes that can be explained by certain chromatin marks - this can be looked at in more detail
Cluster-specific effects: now, instead of correlating each chromatin mark against drug-induced change, I try to correlate the drug-induced change against the chromatin clusters
## Warning in dcast(clusters, `unique(indel.data$barcode)` ~ cluster): The dcast
## generic in data.table has been passed a data.frame and will attempt to redirect
## to the reshape2::dcast; please note that reshape2 is deprecated, and this
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## reshape2::dcast(clusters). In the next version, this warning will become an
## error.## Using 'cluster' as value column. Use 'value.var' to override
## [1] 0.08515303## Df Sum Sq Mean Sq F value Pr(>F)
## cluster 5 2.370 0.4741 5.77 0.000759 ***
## Residuals 30 2.465 0.0822
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Again, some interesting stuff
HDAC vs Integration 17
# H3K27me3 seems to correlate with the logratio change induced by HDACs
Correlation plots individual drugs
HDAC correlation
## Warning in dcast(., Var2 ~ Drug): The dcast generic in data.table has been
## passed a data.frame and will attempt to redirect to the reshape2::dcast; please
## note that reshape2 is deprecated, and this redirection is now deprecated as
## well. Please do this redirection yourself like reshape2::dcast(.). In the next
## version, this warning will become an error.## Using 'logratio.platenorm' as value column. Use 'value.var' to override## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
## continue using melt methods from reshape2 while both libraries are attached,
## e.g. melt.list, you can prepend the namespace like reshape2::melt(.). In the
## next version, this warning will become an error.## Using ChIP as id variables
## Warning in melt(h3k27.data, id.vars = c("rowname", "H3K27me3")): The melt
## generic in data.table has been passed a data.frame and will attempt to redirect
## to the relevant reshape2 method; please note that reshape2 is deprecated, and
## this redirection is now deprecated as well. To continue using melt methods from
## reshape2 while both libraries are attached, e.g. melt.list, you can prepend the
## namespace like reshape2::melt(h3k27.data). In the next version, this warning
## will become an error.
MC-1293 HDAC1 correlation
## Warning in melt(.): The melt generic in data.table has been passed a data.frame
## and will attempt to redirect to the relevant reshape2 method; please note that
## reshape2 is deprecated, and this redirection is now deprecated as well. To
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## e.g. melt.list, you can prepend the namespace like reshape2::melt(.). In the
## next version, this warning will become an error.## Using integration as id variables
Drug dose response
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## Warning in dcast(., barcode ~ Drug, value.var = "mean.logratio.bc.drug"): The
## dcast generic in data.table has been passed a data.frame and will attempt to
## redirect to the reshape2::dcast; please note that reshape2 is deprecated, and
## this redirection is now deprecated as well. Please do this redirection yourself
## like reshape2::dcast(.). In the next version, this warning will become an error.
## Warning in dcast(., barcode ~ Drug, value.var = "mean.logratio.bc.drug"): The
## dcast generic in data.table has been passed a data.frame and will attempt to
## redirect to the reshape2::dcast; please note that reshape2 is deprecated, and
## this redirection is now deprecated as well. Please do this redirection yourself
## like reshape2::dcast(.). In the next version, this warning will become an error.
## Warning in dcast(., barcode ~ Drug, value.var = "mean.logratio.bc.drug"): The
## dcast generic in data.table has been passed a data.frame and will attempt to
## redirect to the reshape2::dcast; please note that reshape2 is deprecated, and
## this redirection is now deprecated as well. Please do this redirection yourself
## like reshape2::dcast(.). In the next version, this warning will become an error.## Warning in melt(., variable.name = "Drug", value.name = "cor"): The melt generic
## in data.table has been passed a data.frame and will attempt to redirect to the
## relevant reshape2 method; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. To continue using melt methods from
## reshape2 while both libraries are attached, e.g. melt.list, you can prepend the
## namespace like reshape2::melt(.). In the next version, this warning will become
## an error.## Using ChIP as id variables## Warning in melt(., variable.name = "Drug", value.name = "cor"): The melt generic
## in data.table has been passed a data.frame and will attempt to redirect to the
## relevant reshape2 method; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. To continue using melt methods from
## reshape2 while both libraries are attached, e.g. melt.list, you can prepend the
## namespace like reshape2::melt(.). In the next version, this warning will become
## an error.## Using ChIP as id variables## Warning in melt(., variable.name = "Drug", value.name = "cor"): The melt generic
## in data.table has been passed a data.frame and will attempt to redirect to the
## relevant reshape2 method; please note that reshape2 is deprecated, and this
## redirection is now deprecated as well. To continue using melt methods from
## reshape2 while both libraries are attached, e.g. melt.list, you can prepend the
## namespace like reshape2::melt(.). In the next version, this warning will become
## an error.## Using ChIP as id variables
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
Exporting potential data.
Session Info
## [1] "Run time: 29.28544 secs"## [1] "/DATA/usr/m.trauernicht/projects/EpiScreen/code/epigenetic-screening-on-trip-clone"## [1] "Fri May 1 13:40:45 2020"## R version 3.6.3 (2020-02-29)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.6 LTS
##
## Matrix products: default
## BLAS: /usr/lib/libblas/libblas.so.3.6.0
## LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] parallel grid stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] Laurae_0.0.0.9001 ggpubr_0.2.5 magrittr_1.5
## [4] tibble_3.0.1 ggforce_0.3.1 VennDiagram_1.6.20
## [7] futile.logger_1.4.3 tidyr_1.0.0 Pigengene_1.10.0
## [10] graph_1.62.0 BiocGenerics_0.30.0 RColorBrewer_1.1-2
## [13] gridExtra_2.3 gridGraphics_0.4-1 pheatmap_1.0.12
## [16] circlize_0.4.8 ComplexHeatmap_2.0.0 data.table_1.12.8
## [19] ggbeeswarm_0.6.0 ggplot2_3.2.1 outliers_0.14
## [22] dplyr_0.8.5
##
## loaded via a namespace (and not attached):
## [1] Cubist_0.2.3 colorspace_1.4-1 ggsignif_0.6.0
## [4] rjson_0.2.20 ellipsis_0.3.0 dynamicTreeCut_1.63-1
## [7] htmlTable_1.13.3 GlobalOptions_0.1.1 base64enc_0.1-3
## [10] clue_0.3-57 rstudioapi_0.10 farver_2.0.1
## [13] bit64_0.9-7 AnnotationDbi_1.46.1 mvtnorm_1.0-12
## [16] codetools_0.2-16 splines_3.6.3 doParallel_1.0.15
## [19] impute_1.58.0 robustbase_0.93-5 libcoin_1.0-5
## [22] knitr_1.28 polyclip_1.10-0 Formula_1.2-3
## [25] WGCNA_1.68 cluster_2.1.0 GO.db_3.8.2
## [28] png_0.1-7 rrcov_1.4-9 compiler_3.6.3
## [31] backports_1.1.5 assertthat_0.2.1 Matrix_1.2-18
## [34] lazyeval_0.2.2 tweenr_1.0.1 formatR_1.7
## [37] acepack_1.4.1 htmltools_0.4.0 tools_3.6.3
## [40] partykit_1.2-5 gtable_0.3.0 glue_1.3.1
## [43] reshape2_1.4.4 Rcpp_1.0.3 Biobase_2.44.0
## [46] vctrs_0.2.4 preprocessCore_1.46.0 iterators_1.0.12
## [49] inum_1.0-1 xfun_0.12 fastcluster_1.1.25
## [52] stringr_1.4.0 lifecycle_0.2.0 DEoptimR_1.0-8
## [55] MASS_7.3-51.5 scales_1.1.0 lambda.r_1.2.4
## [58] yaml_2.2.0 C50_0.1.3 memoise_1.1.0
## [61] rpart_4.1-15 latticeExtra_0.6-29 stringi_1.4.6
## [64] RSQLite_2.2.0 S4Vectors_0.22.1 pcaPP_1.9-73
## [67] foreach_1.4.7 checkmate_1.9.4 shape_1.4.4
## [70] rlang_0.4.5 pkgconfig_2.0.3 matrixStats_0.55.0
## [73] evaluate_0.14 lattice_0.20-38 purrr_0.3.3
## [76] labeling_0.3 htmlwidgets_1.5.1 bit_1.1-15
## [79] tidyselect_0.2.5 robust_0.4-18.2 plyr_1.8.6
## [82] R6_2.4.1 IRanges_2.18.3 Hmisc_4.3-0
## [85] fit.models_0.5-14 DBI_1.1.0 pillar_1.4.3
## [88] foreign_0.8-74 withr_2.1.2 survival_3.1-8
## [91] nnet_7.3-12 crayon_1.3.4 bnlearn_4.5
## [94] futile.options_1.0.1 rmarkdown_2.0 jpeg_0.1-8.1
## [97] GetoptLong_0.1.8 blob_1.2.0 Rgraphviz_2.28.0
## [100] digest_0.6.23 stats4_3.6.3 munsell_0.5.0
## [103] beeswarm_0.2.3 vipor_0.4.5